Aluguel de motocicletas para aplicativos de mobilidade urbana: uma análise de viabilidade financeira

Abstract

This Final Course Project (TCC) addresses the financial feasibility analysis of motorcycle rentals for urban mobility applications. The research incorporates economic, financial, and market variables to provide a holistic view of the economic sustainability of this type of venture. The analysis highlights the importance of adapting to constantly changing economic scenarios, considering transformations in urban dynamics and changes in vehicle ownership preferences. The methodological procedures included market data collection, revenue and cost projection, preparation of the income statement, and cash flow analysis. The economic feasibility analysis was based on Net Present Value (NPV), Internal Rate of Return (IRR), and Discounted Payback indicators. The evaluation included a sensitivity analysis considering three distinct scenarios: pessimistic, realistic, and optimistic. In the pessimistic scenario, with a motorcycle occupancy rate of 90%, the NPV was R$ 5,930.75. In the realistic scenario, with an occupancy rate of 100%, the NPV reached R$ 35,382.90. In the optimistic scenario, with a higher occupancy rate, the NPV was R$ 91,699.80. These results show that even under unfavorable conditions, the project remains financially viable. In the most likely scenario (realistic), the business model was considered viable, achieving a positive NPV of R$ 57,334.07, an IRR of 35.58% per year, and a discounted payback period of 2 years. The contribution of this study lies in providing a foundation for decision-making in a dynamic and constantly evolving sector, which, due to its recent and innovative nature, lacks analyses on the financial economic viability of such a business model. The inclusion of the sensitivity analysis reinforces the robustness of the study, offering a comprehensive view of the potential impacts of variations in critical factors and allowing for more informed and effective strategies for managing the motorcycle rental business for app drivers.